Robust Design of Advanced Thermoelectric Conversion Systems: Probabilistic Design Impacts on Specific Power and Power Flux Optimization

Abstract

AbstractAdvanced, direct thermal energy conversion technologies are receiving increased research attention in order to recover waste thermal energy in advanced vehicles and industrial processes. Advanced thermoelectric (TE) systems necessarily require integrated system-level analyses to establish accurate optimum system designs. Past system-level design and analysis has relied on well-defined deterministic input parameters even though many critically important environmental and system design parameters in the above mentioned applications are often randomly variable, sometimes according to complex relationships, rather than discrete, well-known deterministic variables. This work describes new research and development creating techniques and capabilities for probabilistic design and analysis of advanced TE power generation systems to quantify the effects of randomly uncertain design inputs in determining more robust optimum TE system designs and expected outputs. Selected case studies involving stochastic TE .material properties demonstrate key stochastic material impacts on power, optimum TE area, specific power, and power flux in the TE design optimization process. Magnitudes and directions of these design modifications are quantified for selected TE system design analysis cases.